McDonald's Global Office in India
Website:
corporate.mcdonalds.com
Company:
https://www.linkedin.com/company/mcdonald-s-global-office-in-india
Seniority: Mid-Senior level
Industries: Restaurants
Job details:
About Us:
McDonald’s is proud to be one of the most recognized brands in the world, with restaurants in over 100 countries that serve 70 million customers daily. We continue to operate from a position of strength. Our updated growth strategy is focused on staying ahead of what our customers want and realizing further growth potential. Our relentless ambition is why McDonald’s remains one of the world’s leading corporations after almost 70 years. Joining McDonald's means thinking big and preparing for a career that can have influence around the world.
At McDonald’s, we see every day as a chance to create positive impact. We lead through our values centered on inclusivity, service, integrity, community and family. From support of Ronald McDonald House Charities to our Youth Opportunity project and sustainability initiatives, our values keep us dedicated to using our scale for good: good for our customers, people, industry and planet.
Work location: Hyderabad, India
Work hours: Regular
Work pattern: Full time role.
Work mode: Hybrid.
Position Summary:
AI/ML Platform Lead
We are seeking an experienced AI & ML Platform Lead to drive the strategy, architecture, engineering, and enablement of enterprise AI/ML platform capabilities on Google Cloud Platform. This role is responsible for building and managing scalable AI/ML platform services, governance controls, development standards, self-service capabilities, and platform automation that enable Data Science and AI/ML Operations teams to rapidly build, deploy, and manage AI solutions securely and efficiently.
Who we’re looking for:
Primary Responsibilities:
Platform Strategy & Architecture:
- Define and drive the AI/ML platform strategy, roadmap, standards, and architecture.
- Establish reusable platform services, patterns, and reference architectures for AI/ML development.
- Design scalable, secure, and resilient AI/ML platform capabilities leveraging Vertex AI and GCP services.
- Evaluate and integrate emerging AI technologies and platform capabilities.
AI/ML Platform Engineering:
- Build and manage enterprise AI/ML platform services including development environments, workbenches, model registries, feature stores, pipelines frameworks, and inference infrastructure.
- Develop reusable platform components, templates, accelerators, and automation frameworks.
- Enable standardized development and deployment patterns across AI teams.
- Ensure platform scalability, reliability, availability, and maintainability.
Platform Governance & Controls:
- Establish platform governance standards, guardrails, and onboarding processes.
- Define access management, security controls, auditability, and compliance requirements for AI/ML platforms.
- Implement platform-level governance for AI agents, models, APIs, and AI services.
- Partner with Security, Risk, Legal, and Enterprise Architecture teams to ensure compliance with organizational standards.
Self-Service & Enablement:
- Develop self-service onboarding capabilities for AI engineers and data scientists.
- Create platform documentation, standards, templates, and best practices.
- Drive platform adoption and improve developer experience across AI teams.
- Enable consistent usage patterns and engineering standards across AI initiatives.
Platform Observability & Reliability:
- Establish platform monitoring, logging, alerting, health checks, and operational dashboards.
- Drive platform reliability, capacity planning, resilience, and availability improvements.
- Define platform SLAs, SLOs, and operational readiness requirements.
- Partner with AI/ML Operations teams for operational handoff and support readiness.
Leadership & Stakeholder Management:
- Lead platform engineering initiatives across global teams.
- Mentor engineers and platform specialists.
- Collaborate with Data Engineering, Data Science, Security, Infrastructure, and Operations teams.
- Communicate platform strategy, roadmap, risks, and progress to leadership stakeholders.
Skill:
- 11+ years of experience in AI/ML Platform Engineering, Cloud Platform Engineering, or Data & AI Platform development, preferably on GCP.
- Strong expertise in Google Cloud Platform (GCP), including Vertex AI, BigQuery, Cloud Storage, Dataflow, Cloud Functions, Cloud Run, IAM, Networking, and related platform services.
- 5+ years of experience designing, building, and managing enterprise-scale AI/ML platform capabilities, reusable services, and self-service enablement frameworks.
- Experience implementing platform automation, Infrastructure as Code (Terraform preferred), CI/CD frameworks, and engineering standards for cloud-native platforms.
- Strong experience with source code management, code quality, and engineering best practices using GitHub, GitHub Actions, pytest, SonarQube, or similar tools.
- Experience developing platform services and integrations using Python and APIs.
- Hands-on experience with AI/ML platform services such as Vertex AI Workbench, Model Registry, Feature Store, Vector Search, Generative AI services, and platform enablement capabilities.
- Experience with workflow orchestration and automation platforms such as Astronomer, Airflow, or similar technologies.
- Strong knowledge of containerization and cloud-native technologies, including Docker, Kubernetes, and serverless architectures.
- Experience establishing platform governance, access management, security controls, auditability, and compliance standards for AI/ML platforms.
- Understanding of AI governance, responsible AI principles, and agent lifecycle governance, including onboarding, access management, deployment controls, and observability requirements.
- Experience building reusable templates, accelerators, developer tooling, and self-service capabilities to improve platform adoption and engineering productivity.
- Strong understanding of platform reliability, observability, scalability, availability, and operational readiness.
- Excellent stakeholder management and communication skills, with the ability to collaborate effectively across Data Engineering, Data Science, Security, Infrastructure, Architecture, and business teams.
Why Join Us:
Work with a mission-driven team building cutting-edge technology. Be part of a collaborative, inclusive, and growth-oriented culture.
Additional Information:
McDonald’s is committed to providing qualified individuals with disabilities with reasonable accommodation sto perform the essential functions of their jobs. McDonald’s provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to sex, sex stereotyping, pregnancy (including pregnancy, childbirth, and medical conditions related to pregnancy, childbirth, or breastfeeding), race, color, religion, ancestry or national origin, age, disability status, medical condition, marital status, sexual orientation, gender, gender identity, gender
expression, transgender status, protected military or veteran status, citizenship status, genetic information, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
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